Lead, Cadmium and Zinc Phytotoxicity Alter DNA Methylation Levels to Confer Heavy Metal Tolerance in Wheat
Bibliographic record
Abstract
Being a staple food, wheat (Triticum aestivum) nutritionally fulfills all requirements of human health and also serves as a significant link in the food chain for the ingestion of pollutants by humans and animals. Therefore, the presence of the heavy metals such as lead (Pb) and cadmium (Cd) in soil is not only responsible for the reduction of wheat crop yield but also the potential threat for human and animal health. However, the link between DNA methylation and heavy metal stress tolerance in wheat has not been investigated yet. In this study, eight high yielding wheat varieties were screened based on their phenotype in response to Pb stress. Out of these, Pirsabak 2004 and Fakhar-e-sarhad were identified as Pb resistant and sensitive varieties, respectively. In addition, Pirsabak 2004 and Fakhar-e-sarhad varieties were also found resistant and sensitive to Cd and Zinc (Zn) stress, respectively. Antioxidant activity was decreased in Fakhar-e-sarhad compared with control in response to Pb/Cd/Zn stresses, but Fakhar-e-sarhad and Pirsabak 2004 accumulated similar levels of Pb, Cd and Zn in their roots. The expression of Heavy Metal ATPase 2 (TaHMA2) and ATP-Binding Cassette (TaABCC2/3/4) metal detoxification transporters are significantly upregulated in Pirsabak 2004 compared with Fakhar-e-sarhad and non-treated controls in response to Pb, Cd and Zn metal stresses. Consistent with upregulation of metal detoxification transporters, CG DNA hypomethylation was also found at the promoter region of these transporters in Pirsabak 2004 compared with Fakhar-e-sarhad and non-treated control, which indicates that DNA methylation regulates the expression of metal detoxification transporters to confer resistance against metal toxicity in wheat. This study recommends the farmers to cultivate Pirsabak 2004 variety in metal contaminated soils and also highlights that DNA methylation is associated with metal stress tolerance in wheat.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".